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Added 10 mins ago
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DataVisor

Tech Lead - Software Engineering

Toronto, ON, Canada

Pay: $130,000 to $170,000 CAD / year
Job type: Full-time
Apply by: Mar 22, 2027
Education: Bachelor’s degree
Posting language: English
Posted: Sep 23, 2026

Apply About employer

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Original job description

About DataVisor

DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!

Summary

As part of the Platform Engineering team, you will help build DataVisor's next-generation machine learning platform, combining our proprietary unsupervised machine learning technology with supervised machine learning algorithms to power real-time fraud detection at scale.

As fraud attacks become increasingly sophisticated, real-time detection is more critical than ever. Our platform team is responsible for designing and developing the architecture that makes scalable, real-time detection possible, including streaming systems, storage layers, and training pipelines that support our core detection capabilities.

We are looking for a creative, hands-on engineering leader to help expand our streaming and database systems, improve our core detection algorithms, and automate the end-to-end training process. This role is ideal for someone who enjoys solving complex distributed systems problems, mentoring engineers, and driving technical execution in a high-impact environment.

Join us as we continue to push the boundaries of fraud detection, machine learning infrastructure, and large-scale data processing.

What You'll Do

Own the technical direction of the real-time detection platform, including streaming, storage, and the training pipelines that support it.
Translate product and engineering roadmaps into clear technical plans, milestones, and execution priorities.
Proactively identify technical risks, dependencies, and trade-offs before they impact delivery.
Lead design and architecture reviews, make technical trade-off decisions, and document the reasoning behind key decisions.
Stay hands-on by coding, reviewing code, debugging issues, and supporting the team during production incidents.
Mentor engineers and raise the bar for system design, code quality, operational excellence, and technical execution.
Own the operational health of the platform, including alert quality, on-call load, incident follow-through, and root-cause prevention.
Partner directly with Product, TAM, and customer-facing teams on customer-impacting issues, ensuring clear impact assessment, prioritization, ownership, and next steps.
Define how the team uses AI agents and AI-assisted tools in engineering workflows, including verification standards and safe usage practices.
Build, evaluate, and improve LLM- and agent-assisted tools for engineering and operations use cases, such as triage, root-cause analysis, alert summarization, and evaluation harnesses.

Requirements

8+ years of software development experience.
2+ years of technical leadership experience as a tech lead, staff engineer, engineering manager, or similar role.
Proven ability to lead technical outcomes across a team, including work you did not personally implement.
Deep production experience with Java, along with working proficiency in Python and Shell scripting.
Experience designing, building, shipping, and operating distributed real-time systems at scale.
Strong knowledge of computer systems, relational databases, and SQL.
Experience building and optimizing multithreaded and concurrent applications.
Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka.
Experience with the Spring Framework.
Demonstrated use of AI coding tools such as Claude Code, Cursor, GitHub Copilot, or similar tools in real production work.
Ability to set team-level standards for AI-assisted engineering, including how tools are used, how outputs are verified, and when AI-generated suggestions should be rejected.
Strong verification discipline, with the ability to validate model outputs against source code, logs, documentation, and production behavior.
Bachelor's degree in Computer Science or a related field is required.

Preferred Qualifications

Experience in fraud, risk, payments, financial services, or another domain where false negatives carry significant business or customer impact.
Experience owning ML platforms or large-scale training pipelines.
Experience with Kubernetes.
Experience building with LLM APIs, agent frameworks, tool calling, RAG, or MCP.
Experience writing evaluations or regression tests for non-deterministic systems.
Experience hiring, managing, or mentoring engineers.
Experience with test-driven development

Benefits

Base salary range: $130,000-$170,000, commensurate with experience
Health insurance, PTO, Equity

Apply About employer

More about this job

Responsibilities

Lead the technical direction and delivery of the real-time detection platform, including streaming, storage, and machine-learning training pipelines, while remaining hands-on with coding, reviews, and production support. Mentor engineers, improve operational health, partner with product and customer-facing teams, and establish safe, verifiable use of AI-assisted engineering tools.

Requirements

Requires 8+ years of software development experience, 2+ years of technical leadership, strong production experience with Java, and proficiency in Python and Shell scripting. Candidates must have experience with large-scale distributed real-time systems, databases and SQL, concurrency, Spring, and at least one of Cassandra, Yugabyte, Flink, Spark, or Kafka; a bachelor's degree in Computer Science or a related field is required.

Skills

Java
Python
Shell Scripting
Distributed Systems
Real-Time Systems
Relational Databases
SQL
Multithreading
Concurrency
Cassandra
Yugabyte
Apache Flink
Apache Spark
Apache Kafka
Spring Framework
Technical Leadership

Benefits

Health Insurance
Paid Time Off
Equity

Visa sponsorship

Not detected in the job text

Keywords

Java
Python
Shell Scripting
Distributed Systems
Real-Time Detection
Streaming Systems
Storage Systems
Machine Learning
Training Pipelines
Fraud Detection
Unsupervised Machine Learning
Supervised Machine Learning
Relational Databases
SQL
Multithreading
Concurrency
Cassandra
Yugabyte
Apache Flink
Apache Spark
Apache Kafka
Spring Framework
Kubernetes
Large-Scale Data Processing
LLM APIs
AI Agents
Retrieval-Augmented Generation
Model Context Protocol
Root-Cause Analysis
Test-Driven Development

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